Publications by authors named "Maria E Ruiz-Echartea"

MicroRNA-mediated post-transcriptional regulation of lung alveolar type 2 (AT2) and AT1 cell differentiation remains understudied. Here, we demonstrate that the let-7 miRNA family plays a homeostatic role in AT2 quiescence by preventing the uncontrolled accumulation of AT2 transitional cells and promoting AT1 differentiation. Using mouse and organoid models, we show that genetic ablation of let-7a1/let-7f1/let-7d cluster (let-7afd) in AT2 cells prevents AT1 differentiation and leads to KRT8 transitional cell accumulation in progressive pulmonary fibrosis.

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Background: Exposomes are critical drivers of carcinogenesis. However, how they modulate tumor behavior remains unclear. Extensive clinical data show cigarette smoke to be a key exposome that promotes aggressive tumors, higher rates of metastasis, reduced response to chemoradiotherapy, and suppressed anti-tumor immunity.

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Analysis of lung alveolar type 2 (AT2) progenitor stem cells has highlighted fundamental mechanisms that direct their differentiation into alveolar type 1 cells (AT1s) in lung repair and disease. However, microRNA (miRNA) mediated post-transcriptional mechanisms which govern this nexus remain understudied. We show here that the miRNA family serves a homeostatic role in governance of AT2 quiescence, specifically by preventing the uncontrolled accumulation of AT2 transitional cells and by promoting AT1 differentiation.

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The transcription repressor REST in the dorsal root ganglion (DRG) is upregulated by peripheral nerve injury and promotes the development of chronic pain. However, the genes targeted by REST in neuropathic pain development remain unclear. The expression levels of 4 opioid receptor (Oprm1, Oprd1, Oprl1, Oprk1) and the cannabinoid CB1 receptor (Cnr1) genes in the DRG regulate nociception.

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Protein docking algorithms aim to predict the 3D structure of a protein complex from the structures of its separated components. In the past, most docking algorithms focused on docking pairs of proteins to form dimeric complexes. However, attention is now turning towards the more difficult problem of using docking methods to predict the structures of multicomponent complexes.

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Article Synopsis
  • The CAPRI Round 46 involved 20 protein assembly targets, blending 14 homo-oligomers with 6 heterocomplexes, highlighting challenges in modeling.
  • A significant number of models (~2000 per target) were submitted by about 30 teams, with better performance seen in easier targets but struggles with complex compositions, as evidenced by only 3 out of 11 difficult targets yielding medium to high-quality models.
  • Analysis revealed a decline in prediction quality for binding interface residues compared to previous rounds, pointing to areas needing improvement for future challenges.
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Motivation: Protein-protein docking algorithms aim to predict the 3D structure of a binary complex using the structures of the individual proteins. This typically involves searching and scoring in a 6D space. Many docking algorithms use FFT techniques to exhaustively cover the search space and to accelerate the scoring calculation.

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